The Division of Biostatistics, School of Public Health, at the University of Minnesota has an opening for a non-tenure track (contract) faculty position at the rank of Assistant Professor. Applicants must have a PhD in biostatistics, statistics, or a closely related field, and are required to have at least one of the following research experiences and interests: deep learning/machine learning, statistical genetics/omics or neuroimaging. A successful candidate is expected to play a major role in an NIH-funded project on developing novel statistical methods and applications of deep/machine learning for Alzheimer’s disease neuroimaging and genetics. The candidate will also participate in the Division’s teaching program through classroom instruction and advising graduate students, and will have the opportunity to serve on division and school level committees.
We are strongly committed to recruiting, mentoring, and retaining faculty with a diversity of backgrounds/experiences and support the advancement of the School of Public Health’s recently adopted Strategic Plan for Antiracism (https://www.sph.umn.edu/about/diversity-inclusion/strategy-planning/). We recognize that scholars from historically disadvantaged groups may not have had the same access to opportunities and may have faced substantial barriers on their academic journey, and hence we are committed to carrying out a holistic evaluation of all applicants for the position.
The Division of Biostatistics (www.sph.umn.edu/biostatistics) currently includes 38 graduate faculty and over 60 staff. Faculty regularly publish in the top methodological journals across all major research areas, including causal inference, adaptive clinical trials, statistical genetics and bioinformatics including genomics and proteomics, analysis of spatial and longitudinal data, biomedical imaging, survival analysis, meta-analysis and data synthesis, and mobile health. Division faculty are also active in a wide range of collaborative research projects including high-profile studies of cancer, cardiovascular disease, COVID-19, dentistry and periodontology, psychiatry/psychology, transplantation, chronic and neurodegenerative diseases, and tobacco control. The Division’s Coordinating Center for Biometric Research (CCBR; http://ccbr.biostat.umn.edu/) is considered a field leader in infectious disease clinical trial coordination and has been instrumental in designing and executing seminal vaccine and treatment trials in HIV/AIDS, Ebola, influenza, and COVID-19. Division of Biostatistics faculty have biostatistical leadership roles in major collaborative initiatives, including the Biostatistical Design and Analysis Center (BDAC; https://ctsi.umn.edu/services/statistical-support/biostatistical-support) of the Clinical & Translational Science Institute, the Biostatistics Core of the Masonic Cancer Center (https://ccgg.umn.edu/for-researchers/shared-resources/biostatistics), and the Analytics Core of the Masonic Institute for the Developing Brain (https://midb.umn.edu/research/analytics-core).
The Division offers MS and PhD degrees in Biostatistics, with a current enrollment of 96 students (45 MS, 51 PhD). Students come to our programs from top undergraduate and graduate institutions across the U.S. and around the world, attracted by the quality of our faculty, a reasonable student-faculty ratio, our dedication to student success, and the modest cost of living in the Twin Cities. Division students regularly win prestigious student paper awards at top national and international conferences; approximately half pursue careers in academia, and half choose paths in private industry and government. In Fall 2022, the Division will welcome its first incoming class pursuing the Masters of Public Health (MPH) in Public Health Data Science, a program focused on providing future public health practitioners with more advanced programming and data analysis skills.
The Division of Biostatistics is located on the main University of Minnesota campus, which straddles the Mississippi River near downtown Minneapolis. Campus is served by plentiful public transportation, including a light rail line with a stop less than 5 minutes’ walk from Division offices. On-campus parking is also readily available on a contract or daily fee basis. The Twin Cities of Minneapolis and St. Paul offer all the usual amenities of a major metropolitan area; one notable highlight is the urban parks system, which has frequently been ranked #1 in the nation. Livable neighborhoods are diverse and widespread, and housing prices remain moderate compared to other similarly sized metro areas. The salary range for these positions will be very competitive, and the University of Minnesota offers excellent fringe benefits.
The University of Minnesota offers a comprehensive benefits package including:
Competitive wages, paid holidays, vacation and sick leave
Low cost medical, dental, and pharmacy plans
Health care and dependent daycare flexible spending accounts
Excellent retirement plans with employer match
Disability and employer paid life insurance
Wellbeing program with reduced insurance premiums
Tuition reimbursement opportunities covering 75%-100% of eligible tuition
Applicants must have a PhD in biostatistics, statistics, or a closely related field, and are required to have at least one of the following research experiences and interests: deep learning/machine learning, statistical genetics/omics or neuroimaging. A successful candidate is expected to play a major role in an NIH-funded project on developing novel statistical methods and applications of deep/machine learning for Alzheimer’s disease neuroimaging and genetics. The candidate will also participate in the Division’s teaching program through classroom instruction and advising graduate students, and will have the opportunity to serve on division and school level committees.
The University of Minnesota, founded in the belief that all people are enriched by understanding, is dedicated to the advancement of learning and the search for truth; to the sharing of this knowledge through education for a diverse community; and to the application of this knowledge to benefit the people of the state, the nation, and the world.